$npx skillfedfor your agent

fastmcp

The fast, Pythonic way to build MCP servers and clients.

Worth itPyPI Artificial IntelligenceReleased Aug 202688.7M downloads / moApache-2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — fastmcp-3.4.7-py3-none-any.whl
v3.4.7 · released 2026-08-10 · Python >=3.10 · 1 runtime deps: fastmcp-slim

Yes. FastMCP is actively maintained with a recent release, has zero known vulnerabilities, and uses a permissive Apache-2.0 license. Low install friction and clear documentation make it a practical choice for anyone building MCP servers or integrating LLMs with Python tools. The framework is production-ready and backed by Prefect.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later.
  • Low friction installation as a pure Python wheel.
  • Actively maintained with a release 4 days ago; the project is in the top 1000 on PyPI and is incorporated into the official MCP Python SDK.

License · maintenance · safety

Apache-2.0 (permissive) — Apache-2.0 (permissive) allows commercial use, modification, and distribution with minimal restrictions—suitable for most production scenarios.

last release 2026-08-10 (4 days) · last repo commit 2026-08-14 · 27,207 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 88,710,190 downloads/mo, #384 on PyPI

Verify before relying

pip install fastmcp

from fastmcp import FastMCP

mcp = FastMCP("Demo")

@mcp.tool
def add(a: int, b: int) -> int:
    """Add two numbers"""
    return a + b

if __name__ == "__main__":
    mcp.run()
  • Whether fastmcp-slim (the runtime dependency) is a lighter variant or a required companion package.
  • Specific transport and authentication mechanisms supported beyond 'protocol lifecycle management'.
  • Whether the framework handles both synchronous and asynchronous tool definitions.
  • Exact monthly download volume and current adoption metrics.
Same gist for agents: .md · .json

What it is and what it does

FastMCP is a production-ready Python framework for building Model Context Protocol servers, clients, and applications. It wraps Python functions into MCP-compliant tools, resources, and prompts with automatic schema generation, validation, and documentation. The framework handles protocol negotiation, authentication, and lifecycle management, allowing developers to focus on business logic rather than MCP infrastructure.

The package is designed for three use patterns: servers that expose tools to LLMs, clients that connect to any MCP server locally or remotely, and apps that render interactive UIs directly in conversations. It supports Python 3.10, 3.11, 3.12, and 3.13, and is actively maintained by Prefect with incorporation into the official MCP Python SDK.

Use it for

  • Build an MCP server that exposes custom Python functions as tools for LLMs to call.
  • Create a client that connects to remote MCP servers and manages protocol handshakes automatically.
  • Develop an interactive application that renders tool UIs directly within an LLM conversation.
  • Prototype and deploy MCP-based agents without writing low-level protocol code.
  • Integrate existing Python business logic into an LLM ecosystem with minimal boilerplate.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

FastMCP is actively maintained with a recent release, has zero known vulnerabilities, and uses a permissive Apache-2.0 license. Low install friction and clear documentation make it a practical choice for anyone building MCP servers or integrating LLMs with Python tools. The framework is production-ready and backed by Prefect.

Install

fastmcp on PyPI

Before you install

Low friction installation as a pure Python wheel. Actively maintained with a release 4 days ago; the project is in the top 1000 on PyPI and is incorporated into the official MCP Python SDK. Requires Python 3.10 or later.

Requires Python 3.10 or later.

License in practice

Apache-2.0 (permissive) allows commercial use, modification, and distribution with minimal restrictions—suitable for most production scenarios.

Quickstart

pip install fastmcp

from fastmcp import FastMCP

mcp = FastMCP("Demo")

@mcp.tool
def add(a: int, b: int) -> int:
    """Add two numbers"""
    return a + b

if __name__ == "__main__":
    mcp.run()

Verify before relying

  • Whether fastmcp-slim (the runtime dependency) is a lighter variant or a required companion package.
  • Specific transport and authentication mechanisms supported beyond 'protocol lifecycle management'.
  • Whether the framework handles both synchronous and asynchronous tool definitions.
  • Exact monthly download volume and current adoption metrics.

Package facts

LicenseApache-2.0 permissive
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependencies
1 package
fastmcp-slim
MaintenanceActively maintained 4 days since the last release
Last repo commit
First released
Downloads88,710,190 / month, #384 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Intended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Artificial IntelligenceTyping :: Typed

Evidence: fastmcp-3.4.7-py3-none-any.whl

Tags

Capabilities
model context protocol frameworkmcp server builderllm tool integrationmcp client librarypython mcp framework
Topics
llm-integrationmcp-protocolagent-framework
PyPI keywords
agentfastmcpllmmcpmcp clientmcp servermodel context protocol

Let your AI agent find packages like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.

wish › “model context protocol framework”

  • fastmcpFastMCP is a Python framework for building Model Context Protocol…
  • arcade-serveArcade Serve provides FastAPI and Model Context Protocol server…
  • mcpBuild and connect to Model Context Protocol servers that expose…

Give your agent the search over MCP, or paste the wish link into any chat.

More Artificial Intelligence packages

litellm With conditions
PyPI · Artificial Intelligence · released Aug 2026

LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.

Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.

MITcompiled wheel
682.8Mdownloads / mo
huggingface-hub Worth it
PyPI · Artificial Intelligence · released Aug 2026

Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.

Install it if you work with Hugging Face Hub models or datasets.

Apache-2.0pure Python · 3.10.0+
442.4Mdownloads / mo
langchain Worth it
PyPI · Python Modules · released Aug 2026

LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.

MITpure Python
315.4Mdownloads / mo
hf-xet With conditions
PyPI · Artificial Intelligence · released Aug 2026

hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.

Apache-2.0compiled wheel · 3.8+
258.4Mdownloads / mo
tokenizers Worth it
PyPI · Artificial Intelligence · released Apr 2026

Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.

Apache-2.0compiled wheel · 3.10+
222.9Mdownloads / mo
transformers Worth it
PyPI · Artificial Intelligence · released Aug 2026

Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.

Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.

permissive licensepure Python · 3.10.0+
186.6Mdownloads / mo

See also fastmcp-extensions · fastmcp-slim · workspace-mcp · mcp-use · langchain-mcp-adapters · fast-agent-mcp · mcp · tilt-mcp · mcp-atlassian · jupyter-server-mcp